Optical cable line dynamic environment simulation method and system based on physical rendering

Abstract

The invention provides an optical cable line dynamic environment simulation method and system based on physical rendering, and relates to the technical field of virtual modeling of electric power communication equipment. Comprising six steps of optical cable line basic data acquisition, dynamic environment parameter modeling, PBR-based material attribute definition, dynamic environment and optical cable interactive simulation, rendering optimization and simulation result verification. The system comprises a data acquisition module, an environmental parameter modeling module, a PBR material definition module, a dynamic interaction simulation module, a rendering optimization module, a result verification module and an application integration module. Real material characteristics of the optical cable and accessories are restored through a physical rendering technology, multi-scene real-time simulation is realized in combination with dynamic environment parameters, the influence and hidden defects of the environment on the optical cable are accurately presented, high-precision visual support is provided for optical cable line inspection, fault early warning and operation and maintenance training, and the method is suitable for popularization and application. And the intelligent level of external operation and maintenance of electric power communication is obviously improved.

Description

Technical Field

[0001] This invention relates to the field of virtual modeling technology for power communication equipment, specifically to a method and system for simulating the dynamic environment of optical cable lines based on physical rendering. Background Technology

[0002] In power communication external line equipment and facilities, optical fiber lines serve as the core link for information transmission, carrying critical services such as power production dispatching, monitoring, and safety. Their operational status directly determines the stability and security of the power system. Currently, optical fiber lines cover a wide area and operate in complex and diverse environments, encompassing various scenarios such as mountainous areas, cities, trenches, and dams. They face multiple environmental challenges, including drastic temperature changes, high salt spray, strong electromagnetic interference, and terrain deformation, which can easily lead to problems such as damage to the optical fiber itself, electrolytic corrosion, and joint failures.

[0003] Traditional optical cable line simulation technology has significant shortcomings: First, it suffers from distorted material reproduction. The use of empirical rendering models results in harsh reflections from metal parts and a lack of realistic light transmission in non-metallic parts, leading to a loss rate of over 40% for key visual information. Second, it suffers from sluggish environmental response. It often uses static environmental parameters and cannot simulate the dynamic impact of environmental changes on optical cables in real time, making it difficult to predict potential faults. Third, it is difficult to identify hidden defects. Defects such as micron-level cracks and slight corrosion have low contrast in traditional simulations and are easily missed. Fourth, it suffers from insufficient rendering performance. The model loads slowly in complex scenes, making it difficult to meet the frame rate requirements of scenarios such as AR inspection and mobile monitoring.

[0004] To address the shortcomings of existing technologies, this invention provides a method and system for simulating the dynamic environment of optical cable lines based on physically based rendering. This method performs physical-level simulations based on the optical properties of real materials, collects relevant data on the optical cable line and its auxiliary equipment, models the dynamic environment parameters of the optical cable line, constructs PBR material models of the optical cable and its auxiliary equipment based on the Bidirectional Reflectance Distribution Function (BRDF) and Bidirectional Scattering Distribution Function (BSDF), defines specific material parameters for different components, simulates the coupling effect between dynamic environment parameters and the optical cable line, and uses ray tracing technology to simulate shadows and reflections under real lighting. The simulation results are verified in three dimensions: visual accuracy, physical consistency, and defect recognition rate. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a method and system for simulating the dynamic environment of optical cable lines based on physical rendering, which solves the problem of lack of material parameter templates for existing power communication equipment, and improves the dynamic response of the environment and the accurate identification of hidden defects.

[0006] The technical solution adopted in this invention is to provide a method for simulating the dynamic environment of optical cable lines based on physical rendering, which includes the following steps: Step S1: Basic data collection for optical cable lines. This involves collecting geometric data, material data, physical property data, and historical operation and maintenance data for the optical cable lines and auxiliary equipment. Geometric data is obtained through laser scanning, drone aerial photography, and manual measurement, including details such as optical cable sag, junction box structure, and trench layout. Material data is obtained through macro photography and material analysis instruments, including parameters such as the reflectivity of aluminum-clad steel wire and the light transmittance of HDPE outer sheath. Physical property data includes the elastic modulus and coefficient of thermal expansion of the optical cable. Historical operation and maintenance data includes fault records and environmental impact logs. Step S2: Dynamic environmental parameter modeling. Identify the environmental types of the optical cable line and establish dynamic environmental parameter models such as temperature, humidity, electromagnetic field, salt spray, and terrain deformation. Environmental parameters are connected to sensor data in real time, and static parameters are obtained from the average of historical environmental databases. The trend of environmental parameter changes is predicted through time series algorithms. Step S3: Define material properties based on PBR. Construct PBR material models for optical cables and auxiliary equipment based on BRDF and BSDF models. Define exclusive material parameters for different components. Configure GGX micro-surface distribution model and Fresnel effect parameters for aluminum-clad steel wire. Construct an anisotropic BRDF model for stainless steel tube optical fiber unit. Use subsurface scattering (SSS) model for HDPE outer sheath. Step S4: Dynamic environment and optical cable interaction simulation, simulating the coupling effect between dynamic environment parameters and optical cable lines, including crystal deposition simulation under salt spray environment, rendering of electro-erosion carbonization trajectory under strong electromagnetic field, optical cable sag deformation simulation under temperature change, and optical cable tensile state simulation under terrain deformation. Step S5: Rendering optimization. Ray tracing technology is used to simulate shadows and reflections under real lighting. Hardware acceleration, visibility culling, and multi-resolution rendering technology are combined to improve rendering efficiency. Image quality is optimized through post-processing such as anti-aliasing, depth of field effects, and color correction. Step S6, Simulation Result Verification: Verify the simulation results from three dimensions: visual accuracy, physical consistency, and defect recognition rate. Visual accuracy is verified by comparing with the actual object to check the material reproduction degree. Physical consistency is verified by comparing mechanical simulation data to check the deformation accuracy. Defect recognition rate is evaluated by the number of latent defects detected.

[0007] A physically based rendering-based dynamic environment simulation system for optical cable lines includes: The data acquisition module is equipped with a laser scanner, drone, macro camera, material analysis instrument and environmental sensor to collect optical cable geometric data, material data, physical property data and real-time environmental data, and supports docking with GIS system and operation and maintenance database to obtain historical data; The environmental parameter modeling module constructs environmental parameter models such as temperature, humidity, electromagnetic field, salt spray, and terrain deformation. It has a built-in time series prediction algorithm to support real-time updates and trend prediction of environmental parameters, and includes a sub-model library for extreme environments. The PBR material definition module integrates BRDF / BSDF parameter configuration tools, provides exclusive material templates for aluminum-clad steel wire, HDPE outer sheath, stainless steel pipe, etc., and supports custom adjustment of material parameters and experimental calibration. The dynamic interactive simulation module, based on a multi-physics coupling algorithm, realizes the interactive simulation of environmental parameters and optical cables. It includes a defect visualization rendering unit that can present hidden defects such as micron-level cracks, corrosion pits, and electrolytic carbonization. The rendering optimization module has a built-in ray tracing engine, equipped with a GPU acceleration unit, and integrates visibility culling, multi-resolution rendering, LOD hierarchical management and post-processing optimization tools to ensure smooth rendering on multiple terminals. Result verification module: includes a visual accuracy verification unit, a physical consistency comparison unit, and a defect recognition rate evaluation unit, automatically generates verification reports, and supports iterative optimization of simulation parameters; The application integration module supports output in formats such as glTF2.0 and USDZ, is compatible with Unity and Unreal Engine development platforms, and can be seamlessly integrated with AR operation and maintenance platforms, remote assistance systems, and virtual training systems. The security protection module uses national cryptographic algorithms SM2 / SM3 / SM4 to encrypt data transmission and storage, and implements hierarchical access control based on the RBAC mechanism to ensure data security.

[0008] Compared with existing technologies, the present invention provides a method and system for simulating the dynamic environment of optical cable lines based on physical rendering, which has the following advantages: 1. This invention constructs a dedicated material model based on PBR technology, which greatly improves the accuracy of high light reflection of aluminum-clad steel wire and the realism of light transmission texture of HDPE outer sheath, effectively solving the problem of material reproduction distortion in traditional simulation, and accurately reproducing the real physical characteristics of optical cables and various accessories.

[0009] 2. This invention constructs a multi-dimensional dynamic environmental parameter model, which integrates data collected by sensors in real time and predicts the trend of environmental changes. It accurately simulates the interaction between various environments such as salt spray and electromagnetic fields and optical cables, and dynamically presents the impact of different environments on the operation of optical cables.

[0010] 3. This invention utilizes an ambient light occlusion algorithm to make latent defects present high-contrast features in simulated scenes, significantly improving the identification effect of latent defects, reducing the probability of false defect judgment, and effectively reducing the risk of missing hidden dangers.

[0011] 4. This invention employs multiple optimization technologies such as LOD grading and hardware acceleration to ensure a smooth rendering experience on both mobile devices and AR glasses, fully meeting the usage needs of different scenarios such as inspection and training.

[0012] 5. This invention can be deeply integrated with AR operation and maintenance platforms and remote assistance systems to realize diversified functions such as fault early warning, path navigation, and virtual training, and promote the transformation of operation and maintenance mode from the traditional method that relies on experience to the intelligent method that relies on data. Attached Figure Description

[0013] The present invention will be further described below with reference to the accompanying drawings and embodiments: Figure 1 This is a flowchart of the dynamic environment simulation method for optical cable lines based on physical rendering according to the present invention; Figure 2 This is a simulation diagram of the dynamic environment interaction effect of the optical cable line of the present invention; Figure 3 This is a schematic diagram comparing the rendering LOD levels of this invention. Detailed Implementation

[0014] To better understand the purpose, system architecture, and functional implementation of this embodiment, the embodiments and features described herein can be combined with each other without conflict. The exemplary embodiments disclosed herein will be described below with reference to the accompanying drawings, including specific technical details disclosed to aid understanding; however, these details should be considered exemplary rather than restrictive. Therefore, those skilled in the art should understand that various improvements and adjustments can be made to the embodiments described herein without departing from the scope and core ideas of the invention. Similarly, for clarity, detailed descriptions of well-known technologies, functions, and structures are omitted in the following description.

[0015] Example 1 Figure 1 This is a flowchart of the dynamic environment simulation method for optical cable lines based on physical rendering according to the present invention.

[0016] like Figure 1 As shown, a method for simulating the dynamic environment of optical cable lines based on physical rendering includes the following steps: Step S1: Acquisition of basic data for optical cable lines. A multi-method collaborative acquisition strategy is adopted to obtain comprehensive basic data of optical cable lines and auxiliary equipment, covering geometry, material, physical properties and the entire life cycle of operation and maintenance. Step S2: Dynamic environmental parameter modeling. This involves identifying typical environmental types of optical cable lines, such as mountainous areas, cities, trenches, and dams, and constructing a multi-dimensional dynamic environmental parameter model to enable real-time updates and trend predictions of environmental data. Step S3: Define material properties based on PBR. Construct PBR material models for optical cables and auxiliary equipment based on BRDF and BSDF models to break through the empirical limitations of traditional rendering and achieve physical-level reproduction of material properties. Step S4: Dynamic environment and optical cable interaction simulation. Multi-physics coupling modeling technology is used to simulate the real-time interaction between dynamic environmental parameters and optical cable lines, accurately presenting the impact of the environment on optical cables and the evolution process of latent defects. Step S5: Rendering optimization, integrating technologies such as ray tracing and hardware acceleration, balancing rendering accuracy and running performance, and meeting the needs of multi-terminal adaptation; Step S6: Simulation result verification. Verification is carried out from three core dimensions: visual accuracy, physical consistency, and defect recognition rate, to ensure that the simulation results meet the requirements of actual application.

[0017] According to an embodiment of the present invention, step S1 includes the following different data acquisitions: Geometric data acquisition: High-precision point cloud data of equipment such as optical cables, junction boxes, and fiber distribution boxes are acquired using laser scanners with an accuracy of ≤0.05mm. Large-scale optical cable routing and terrain data are acquired through drone aerial photography. For obstructed areas such as communication equipment interfaces and narrow trenches, manual supplementary measurements are performed using laser rangefinders to ensure the completeness of detailed data such as optical cable sag, internal structure of junction boxes, and trench layout. Material data acquisition: Take photos of the surface texture of optical cables and accessories with a macro camera, and use material analysis instruments to detect key parameters such as reflectivity and roughness of aluminum-clad steel wire, light transmittance and refractive index of HDPE outer sheath, and texture characteristics of stainless steel pipe. Physical property data acquisition: Collect physical parameters such as the elastic modulus, coefficient of thermal expansion, tensile strength, and sealing performance of the junction box of the optical cable, and determine the parameter thresholds with reference to industry standards such as IEEE1138; Historical Operation and Maintenance Data Collection: Connect to the power and communication operation and maintenance database to obtain data such as optical cable fault records, environmental impact logs, and maintenance records, providing historical reference for dynamic environment simulation.

[0018] Data was collected from a 110kV optical cable line along the coast. Point cloud data of the optical cable and junction box were obtained using a laser scanner. The texture of the HDPE outer sheath was captured by a macro camera. Material analysis instruments were used to test the aluminum-clad steel wire, which showed a reflectivity of 0.85 and a roughness of 0.08. The elastic modulus of the optical cable was collected at 80 GPa, and the coefficient of thermal expansion was 12 × 10⁻⁶. -6 / ℃, connect to the operation and maintenance database to obtain salt spray corrosion fault records for the past 3 years.

[0019] According to an embodiment of the present invention, step S2 includes the following steps: S210, Core Environmental Parameter Modeling: Establish models for five core environmental parameters: temperature, humidity, electromagnetic field, salt spray, and terrain deformation. Temperature covers the extreme range of -40℃ to 70℃, humidity covers the range of 0% to 100%, and electromagnetic field strength is set with safety thresholds according to the power industry's strong electromagnetic interference standards. S220, Parameter Dynamic Update: Real-time access to environmental sensor data deployed at key nodes of the optical cable line, with sensor sampling frequency ≥10Hz and data transmission delay ≤200ms; for areas without sensor coverage, the average value of the historical environmental database is used as static parameters. S230 Trend Prediction: By analyzing the changing patterns of environmental parameters through time series algorithms, the trend of environmental changes in the next 24 hours is predicted, providing data support for the prediction of optical cable line faults; S240, Extreme Environment Sub-model: For special scenarios such as high salt spray in coastal areas, strong temperature difference in mountainous areas, and strong electromagnetic interference in cities, a dedicated extreme environment sub-model is constructed to accurately simulate the impact of harsh environments on optical cables.

[0020] By constructing a dynamic environmental model of salt spray, temperature, humidity, and electromagnetic field, the salt spray concentration parameter is connected to the coastal environmental sensor data in real time. The temperature range is set to 5℃~35℃, the humidity range is 60%~95%, and the electromagnetic field strength is set to ≤10kV / m according to the power industry standard. The salt spray concentration change trend in the next 24 hours is predicted by the LSTM time series algorithm.

[0021] According to an embodiment of the present invention, in step S3, the definition of different materials includes: Aluminum-clad steel wire material definition: Applying the GGX micro-surface distribution model, integrating Fresnel effect and environmental reflection technology, and setting core parameters such as metal reflectivity of 0.8 and roughness of 0.1, the physical accuracy of high-gloss reflection on the metal surface is improved by 90%, and the optical contrast of micro-scratches is improved by 120%. Material definition for stainless steel tube fiber optic unit: Construct an anisotropic BRDF model to simulate directional texture, optimize surface texture rendering accuracy, and improve the visual saliency of abnormal deformation areas by 70%; HDPE outer sheath material definition: The SSS model is used to simulate the light penetration and scattering process, which improves the accuracy of the sheath's light transmission texture by 75% and the visual detectability of internal bubbles and surface cracks by 65%. Junction box material definition: For the metal shell and plastic parts of the junction box, corresponding PBR material parameters are configured to reproduce the texture differences and physical properties of different parts.

[0022] The aluminum-clad steel wire adopts the GGX micro-surface model, with a reflectivity of 0.85 and a roughness of 0.08. The HDPE outer sheath uses the subsurface scattering model, with a light transmittance parameter set to 0.6. The metal shell of the junction box is configured with metal material parameters, and the plastic parts are set with non-metallic material properties.

[0023] According to an embodiment of the present invention, in step S4, the effects of different environments on the optical cable include: Interactive simulation of salt spray environment: In a coastal scenario, the deposition morphology of sodium chloride crystals on the surface of optical cable is accurately reproduced to simulate the aging process of the sheath caused by salt spray corrosion. Interactive simulation of electromagnetic field environment: In areas with strong electromagnetic interference, the trajectory of electro-erosion and carbonization induced by corona discharge is rendered in real time, and the parts with potential discharge hazards are highlighted by high contrast. Interactive simulation of temperature environment: Based on real-time temperature data, the sag shape of the optical cable is dynamically adjusted to simulate the thermal expansion and contraction of the optical cable caused by temperature changes, ensuring that the sag deformation conforms to the laws of mechanics. Interactive simulation of terrain deformation: Combining GIS terrain data, it simulates the tensile effects of terrain subsidence, landslides, etc. on optical cables, and presents the stress state of optical cables in real time. Visualization of latent defects: Through ambient light occlusion algorithms, latent defects such as micron-level cracks and corrosion pits are made to present high-contrast features in simulated scenarios, making them easy for maintenance personnel to identify.

[0024] Figure 2 This is a simulation diagram of the dynamic environment interaction effect of the optical cable line according to the present invention.

[0025] like Figure 2 As shown, Figure 2 (a) To simulate the deposition process of salt spray on the surface of optical cable, a salt spray concentration of 5000 mg / m³ was used to reduce the deposition morphology of sodium chloride crystals on the surface of optical cable, showing the aging and roughening effect of the sheath caused by salt spray corrosion. Figure 2 (b) Real-time display of the electro-erosion and carbonization trajectory of the optical cable sheath under electromagnetic field environment, highlighting the parts with potential discharge hazards through high contrast display. Figure 2 (c) Simulation of optical cable sag deformation in temperature-changing environments dynamically presents the thermal expansion and contraction of the optical cable due to temperature gradients, accurately reproducing the sag deformation. The image enhances the defect area through light and shadow contrast, making previously difficult-to-detect 0.1mm-level micro-cracks and corrosion pits clearly visible, solving the problem of low defect contrast and easy omission in traditional simulations.

[0026] According to an embodiment of the present invention, step S5 integrates technologies such as ray tracing and hardware acceleration, including the following steps: S301, Core Rendering Optimization: Enable ray tracing technology in the Unity engine to simulate shadow and reflection effects under real lighting conditions, and set multiple types of light sources such as sunlight, moonlight, and artificial light sources to restore all-weather lighting scenes; S302, Hardware Acceleration Enhancement: Utilizes the parallel computing power of high-performance GPUs to accelerate ray casting and scene rendering, and combines visibility culling technology to render only objects within the user's field of view; S303, LOD hierarchical management: Three levels of precision are set according to viewing distance. L0 level macro planning geometric error ≤5cm, suitable for regional layout display. L1 level operation and maintenance inspection geometric error ≤1cm, suitable for equipment status inspection. L2 level maintenance training geometric error ≤1mm, suitable for component-level detail display, ensuring mobile rendering frame rate ≥30FPS and AR glasses ≥60FPS. S304. Post-processing optimization: Anti-aliasing algorithms are used to eliminate jagged edges on the image, depth of field effects are used to highlight key equipment components, color correction is used to unify the color balance of the image, and effects such as blurring and sharpening are added as needed to improve inspection efficiency.

[0027] Figure 3 This invention renders a LOD (Level of Detail) comparison diagram.

[0028] like Figure 3 As shown, LOD precision is set to level 3. Figure 3 (a) Level L0 is used for macro-level monitoring of the line. The optical cable line is rendered as a simplified line or a low-poly ribbon, which only expresses the basic route and direction. Key equipment such as junction boxes and towers are simplified to basic geometric shapes or icons, which is suitable for overall layout display, path planning and large-scale scene overview. Figure 3 (b) Level L1 is used for inspection operations. The optical cable has a clear cylindrical structure. The junction box, fiber distribution box and other equipment show the basic external structure and outline of the main components. However, the internal complex structure is simplified or omitted. Medium resolution texture mapping and basic PBR material effects are applied to express the basic texture and color of metal and plastic. However, details such as highlights and reflections may be controlled. It is suitable for daily inspection, external inspection of equipment status and preliminary fault location. Figure 3 (c) A highly detailed L2-level model is used for viewing the internal details of the junction box. Ray tracing is enabled to simulate the effect of sea surface reflected light on the optical cable. Image quality is optimized through anti-aliasing and color correction. The rendering frame rate on the AR glasses reaches 62FPS, which is suitable for refined maintenance operation training, component-level defect detection, and internal structure learning.

[0029] According to an embodiment of the present invention, step S6 involves verification from three core dimensions: visual accuracy, physical consistency, and defect recognition rate, including: Visual accuracy verification involves comparing the simulation results with the actual optical cable and high-definition photographs to check the material reproduction, texture clarity, and lighting realism, ensuring that the visual error is ≤3%. Physical consistency verification: Theoretical data on optical cable deformation and stress are obtained through mechanical simulation tools and compared with simulation results to ensure that the error of physical parameters is ≤5%; Defect recognition rate verification: Select optical cable samples containing latent defects and compare the number of defects detected by the traditional simulation method with that of this method to ensure that the latent defect recognition rate of this method is ≥65% higher than that of the traditional method, and the defect false positive rate is ≤5%; Finally, the verification results are standardized and packaged to generate a visual report. For results that fail, the corresponding steps are returned to adjust the parameters until the requirements are met. The visual accuracy comparison shows a material reproduction error of 2.1%. In the physical consistency verification, the error between the simulated data and the measured data of the optical cable sag is 3.2%. The defect identification rate is 68% higher than that of traditional methods. Three micro-cracks that were missed by traditional simulation were successfully detected. After the verification is passed, a visual operation and maintenance report is generated.

[0030] Example 2 The system's hardware deployment includes servers equipped with Kunpeng 920 CPUs, 64GB of RAM, and 2TB SSDs, running the Galaxy Kylin V10 operating system. Edge devices include two FARO laser scanners, three drones, and ten HoloLens 2AR glasses (IP66 protection, supporting 5G / Wi-Fi). Network equipment uses Huawei S12700 core switches and USG6000E firewalls to build a DMZ zone that isolates the internal and external networks.

[0031] The system's software configuration includes a data acquisition module that deploys laser scanning control software and drone aerial photography software; a PBR material definition module that integrates the Unity 2022 engine and Substance Painter material drawing tool; a dynamic interactive simulation module that incorporates a multiphysics coupling algorithm library; and an application integration module that connects to the power communication AR operation and maintenance platform. Real-time data synchronization is achieved using a Kafka message queue.

[0032] In AR inspection scenarios, maintenance personnel wear HoloLens2 glasses to view dynamic simulated images of optical cables and zoom in on defective areas through gesture interaction; in remote assistance scenarios, experts annotate simulated images on PCs to guide on-site handling of potential salt spray corrosion hazards; in training scenarios, trainees practice maintaining optical cable junction boxes through a simulation system, with the system providing real-time feedback on the operational results.

[0033] This invention accurately restores the material properties of optical cables through physical rendering technology and realizes real-time interactive simulation of multiple scenarios by combining dynamic environment modeling. It solves many pain points of traditional simulation and provides a high-precision and intelligent visualization tool for the operation and maintenance of optical cable lines throughout their entire life cycle. It has important engineering application value and promotion prospects.

[0034] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0035] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A method for simulating the dynamic environment of optical cable lines based on physically based rendering, characterized in that, Includes the following steps: S1 collects geometric data, material data, physical property data, and historical operation and maintenance data of optical cable lines and auxiliary equipment; S2. Based on the environmental type of the optical cable line, establish a dynamic environmental parameter model for temperature, humidity, electromagnetic field, salt spray and terrain deformation, and predict the trend of environmental parameters based on time series algorithm. S3, based on the bidirectional reflection distribution function BRDF and bidirectional scattering distribution function BSDF, constructs a physically based rendering material model of optical cable and auxiliary equipment, and configures corresponding material parameters for different components; S4, simulate the coupling effect between the dynamic environmental parameters and the optical cable line to generate the deformation state and defect evolution results of the optical cable under different environmental conditions; S5 uses ray tracing rendering to optimize the simulation results; S6 validates the simulation results from three dimensions: visual accuracy, physical consistency, and defect recognition rate.

2. The method according to claim 1, characterized in that, In step S1, geometric data is obtained through a combination of laser scanning, drone aerial photography, and manual measurement. The geometric data includes at least information on optical cable sag, junction box structure, and trench layout.

3. The method according to claim 1, characterized in that, In step S2, the dynamic environmental parameter model includes an extreme environment sub-model, which is used to simulate the impact of high salt spray, high temperature difference or strong electromagnetic interference environment on optical cable lines.

4. The method according to claim 1, characterized in that, In step S3, the aluminum-clad steel wire adopts the GGX micro-surface distribution model and is configured with Fresnel reflection parameters, the stainless steel tube fiber unit adopts the anisotropic BRDF model, and the HDPE outer sheath adopts the subsurface scattering model.

5. The method according to claim 1, characterized in that, In step S4, the dynamic environment and optical cable interaction simulation includes at least the salt spray crystal deposition simulation, the electro-erosion carbonization trajectory simulation under the action of electromagnetic field, the optical cable sag deformation simulation caused by temperature change, and the optical cable tensile state simulation caused by terrain deformation.

6. The method according to claim 1, characterized in that, In step S5, the rendering optimization adopts a LOD hierarchical strategy, which automatically switches the model accuracy between macro display level, operation and maintenance inspection level and maintenance training level according to the viewing distance or application scenario.

7. The method according to claim 1, characterized in that, In step S6, the defect identification rate is evaluated by the number of identifiable microcracks, corrosion pits, or electrolytic erosion areas in the statistical simulation results.

8. A dynamic environment simulation system for optical cable lines based on physically based rendering, characterized in that, include: The data acquisition module is used to collect geometric data, material data, physical property data, and real-time environmental data of optical cable lines and auxiliary equipment; The environmental parameter modeling module is used to build dynamic environmental parameter models and predict environmental change trends. The PBR material definition module is used to build physically rendered material models of optical cables and related equipment based on BRDF and BSDF. The dynamic interactive simulation module is used to simulate the coupling effect between dynamic environmental parameters and optical cable lines; The rendering optimization module is used for ray tracing rendering and performance optimization of the simulation results; The results verification module is used to verify the visual accuracy, physical consistency, and defect recognition rate of the simulation results.

9. The system according to claim 8, characterized in that, The rendering optimization module includes a GPU acceleration unit, a visibility culling unit, and a LOD hierarchical management unit to achieve real-time rendering under multi-terminal conditions.

10. The system according to claim 8, characterized in that, The system also includes an application integration module, which outputs simulation results in glTF or USDZ format and integrates them with the AR operation and maintenance platform or virtual training system.

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